Systems Metabolic Engineering Strategies: Integrating Systems and Synthetic Biology with Metabolic Engineering

代谢工程 合成生物学 生物制品 系统生物学 生化工程 计算机科学 代谢通量分析 生物技术 生物 基因组工程 计算生物学 工程类 生物燃料 遗传学 基因组 基因组编辑 基因 内分泌学 新陈代谢
作者
Kyeong Rok Choi,Woo Dae Jang,Dongsoo Yang,Jae Sung Cho,Dahyeon Park,Sang Yup Lee
出处
期刊:Trends in Biotechnology [Elsevier]
卷期号:37 (8): 817-837 被引量:413
标识
DOI:10.1016/j.tibtech.2019.01.003
摘要

HighlightsSystems metabolic engineering, which integrated systems biology, synthetic biology, and evolutionary engineering with traditional metabolic engineering, is facilitating the development of high performance strains.More diverse microorganisms are being used as production host strains, supported by the new genetic tools and strategies.Recent advances in biosynthetic/semisynthetic design strategies are expanding the portfolio of products that can be produced biologically.Evolutionary engineering tools and strategies are facilitating the improvement of strain and enzyme performances.Advances in tools and strategies of omics, in silico metabolic simulation, genetic and genomic engineering, and high-throughput screening are accelerating optimization of metabolic fluxes for the enhanced production of target bioproducts.AbstractMetabolic engineering allows development of microbial strains efficiently producing chemicals and materials, but it requires much time, effort, and cost to make the strains industrially competitive. Systems metabolic engineering, which integrates tools and strategies of systems biology, synthetic biology, and evolutionary engineering with traditional metabolic engineering, has recently been used to facilitate development of high-performance strains. The past decade has witnessed this interdisciplinary strategy continuously being improved toward the development of industrially competitive overproducer strains. In this article, current trends in systems metabolic engineering including tools and strategies are reviewed, focusing on recent developments in selection of host strains, metabolic pathway reconstruction, tolerance enhancement, and metabolic flux optimization. Also, future challenges and prospects are discussed.
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